Ouroboros, an apt symbol for AI model collapse

by Ariella Brown

AI hits the ouroboros (sometimes written uroboros) stage. You've likely seen it in the form of a snake in a circle, eating its own tail. The ancient symbol also sometimes showed dragons or a wyvern, so I chose this engraving by Lucas Jennis intended to represent mercury in the 1625 alchemical tract "De Lapide Philosophico," for my illustration instead of just going with something as prosaic as "model collapse"

To get a bit meta and bring generative AI into the picture (pun intended, I'm afraid) here's an ouroboros image
made with generative AI. ked Google

Model collapse is what the researchers who published their take on this in Nature called the phenomenon of large language models (LLMs) doing the equivalent of eating their own tails when ingesting LLM output for new generation. They insist that the models should be limited to"data collected about genuine human interactions."

From the abstract:
"Here we consider what may happen to GPT-{n} once LLMs contribute much of the text found online. We find that indiscriminate use of model-generated content in training causes irreversible defects in the resulting models, in which tails of the original content distribution disappear. We refer to this effect as ‘model collapse’ and show that it can occur in LLMs as well as in variational autoencoders (VAEs) and Gaussian mixture models (GMMs). We build theoretical intuition behind the phenomenon and portray its ubiquity among all learned generative models. We demonstrate that it must be taken seriously if we are to sustain the benefits of training from large-scale data scraped from the web. Indeed, the value of data collected about genuine human interactions with systems will be increasingly valuable in the presence of LLM-generated content in data crawled from the Internet."

Shumailov, I., Shumaylov, Z., Zhao, Y. et al. AI models collapse when trained on recursively generated data. Nature 631, 755–759 (2024).

Let me know in the comments which illustration you like more. 

How to increase traffic 16,500%: clickbait vs. reality

 

by Ariella Brown

I just attended an event with the title " Information Gain Content: How to Increase Traffic 16,500% by Going Above & Beyond with Bernard Huang." Did the session live up to its clickbait title?

Not at all. 

This wasn't necessarily Bernard Huang's fault. The presentation was hosted by the Top of the Funnel group that favors these types of large numbers that sound just specific enough that people may believe they are real.

Earlier this month, it offered "Social Copywriting Secrets: Building an Audience of 114,985 with Eddie Shleyner" I attended that one, too, and there was nothing in it that justified that number as the guaranteed result of some tactic you could apply. Shleyner just emphasized sticking to good, authentic storytelling to keep your audience engaged.

There were no easy-to-apply tricks in this session. If anything, it was about the reason the old tricks no longer work.  Huang explained that Google is currently applying its stated standard of Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) in the context of its AI overview.

My main takeaway from this session was not that it's easy to increase your traffic on Google but that it simply has switched one set of algorithmic rules for another, now including its own AI reads on content and that this is not necessarily a good thing.

What bad about this? 

The bottom line is that Google is relying very heavily on consensus as well as pre-established authority. That means that it is very easy for the sites that have already built up big audiences and strong rankings on Google to leverage that to put out proclamations that will be accepted as true, especially when they are -- inevitably -- echoed by the wannabee followers and all those who pretend to be thought leaders by parroting what influencers already say.


In other words, truly original thoughts by those who are not just reinforcing group think will likely be buried. I did raise this question and wasn't wholly reassured by the answer. It was that, yes, Google expects all points of consensus on a particular topic to be represented. If they are not present, your content will be an outcast. The only way you have a chance to be noted is if you play the contrarian game by refuting the consensus views point by point. Not giving it that nod is SEO suicide.

And so we the current state of search is one that aims to homogenize information according to preset parameters from those already granted expert status where those who are not in line with the consensus will be buried in the obscurity of high number page results. 

This is truly the opposite of a democratic platform in which understanding of history and current events is allowed to rise or fall based solely on its own merit rather than the pre-established narrative. George Patton would be appalled. He's the one who said: "If everyone is thinking alike, then somebody isn't thinking."

Google's algorithms are designed to reward those who follow in the paths preset by others rather than really thinking for themselves. 

P.S. For the story behind the illustration above, see my LinkedIn post. 

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You can also follow Ariella Brown.  

Aim higher than SEO for your marketing content

You know, Jane Austen could have opened "Pride and Prejudice" with the standard line, "Once upon a time there was a family with five girls and no sons to inherit the estate that they depended on for their support." She didn't.

https://www.zazzle.com/pride_and_prejudice_tote_bag-149363338488539996

Instead of sticking with the safe formulation, she crafted one of the most memorable openers for a novel that also gives the readers a taste of her wit and sense of irony. That opening line is Austen's brand in a nutshell.

This is what businesses should be striving for in their opening lines on their sites and their reports. Generative AI will not deliver that because it will work off pre-existing models. Simply tweaking that output will still not result in something truly fresh, though it may be just good enough to not incur the generative AI penalty Google has promised to deliver for those who aspire to achieve high SEO results.

Achieving SEO goals is not the same as making a memorable impression on your target audience when they click through to your site or blog.

What impresses Google is not necessarily going to move your target market to establish a relationship with your brand. The content that does can only be produced by a combination of analytics and human creativity.

You can't just be content with optimizing for search engines by following SEO guidelines when you need RO -- responsiveness optimization -- that requires blazing your own brand path.

That's what Write Way branding and marketing is all about. Learn more about my business offerings here.

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Bard brings in the clowns for my query on ICP

 

by Ariella Brown

I've been reading Built to Last, a 1994 book about  successful businesses. None of the business models relied on the internet, and many of them already had many decades of history behind them. I noticed that the jargon in the book is quite different from today's.

For example, there is not a single mention of ICP (ideal customer profile). That made me curious. Did this term only emerge after the book's publication?

I turned to Bard ( see why here) for the answer, which also explains why this term emerged only in the post-internet world. This is what it wrote, and I have to admit being somewhat amused by the somewhat pushy CTA at the end and if the "I" is meant to be the AI itself:

The term "ideal customer profile" (ICP) was first used in the early 2000s by marketing and sales professionals. It was originally used to describe a hypothetical company that would be the perfect fit for a particular product or service. However, the term has since been adopted by businesses of all sizes and industries.

 

There are a few reasons why businesses started referring to ICPs. First, it became clear that not all customers are created equal. Some customers are more likely to be profitable than others. By understanding the characteristics of their ideal customers, businesses can focus their marketing and sales efforts on the most likely to convert.

 

Second, the rise of the internet made it easier for businesses to collect data about their customers. This data can be used to create detailed ICPs that take into account factors such as company size, industry, location, and pain points.
Finally, the increasing complexity of the marketplace made it more difficult for businesses to compete on price alone. By understanding their ideal customers and their needs, businesses can differentiate themselves from the competition and offer products and services that are truly valuable.

 

Today, ICPs are an essential part of any successful marketing and sales strategy. By creating a detailed ICP, businesses can improve their targeting, messaging, and conversion rates. This can lead to increased sales, improved customer satisfaction, and a stronger bottom line.
Here are some of the benefits of using an ICP:

 

Increased sales: By targeting your marketing and sales efforts to your ideal customers, you can increase your chances of closing deals.

 

Improved customer satisfaction: When you understand the needs of your ideal customers, you can deliver products and services that are more likely to meet their expectations.

 

Stronger bottom line: By improving your sales and customer satisfaction, you can increase your profits.

 

If you're not already using an ICP, I encourage you to start today. It's a simple but powerful tool that can help you take your business to the next level.

Notice that Bard is very bullish on ICPs, even pushy, I'd venture to say. That turns out to be a bit funny when it fails to recognize the acronym for my next query for a more recent business bible.

Clowns you say? 

I also recently read The Hard Thing About Hard Things published in 2014. I don't recollect a single mention of  ICP. Just to be sure, I asked Bard, which shows a kind of split personality when it comes to recalling acronyms. This was its response:

No, the book "The Hard Thing About Hard Things" by Ben Horowitz does not mention ICP. ICP stands for Insane Clown Posse, a hip hop duo from Detroit, Michigan. The book is about the challenges of running a startup company, and ICP is not relevant to that topic.
The book does mention a few other bands, such as The Beatles and The Rolling Stones. However, these bands are mentioned in the context of how they have influenced the music industry. ICP is not mentioned in the book at all.

Knowing that when you work with generative AI you have to try your prompt multiple times, I get it another whirl and wrote out "ideal customer profile" for the query. Now Bard grasped what I was asking and responded:

"The book "The Hard Thing About Hard Things" by Ben Horowitz does not explicitly mention the need for an ideal customer profile. However, the book does talk about the importance of knowing your target market and understanding their needs. This is essentially what an ideal customer profile is.

 

In Chapter 1, Horowitz writes, "The first thing you need to do is figure out who you're building for." He goes on to say that you need to "understand their pain, their goals, and their constraints." This is all information that would be included in an ideal customer profile.
In Chapter 2, Horowitz writes about the importance of "building a product that people actually want." He says that you need to "get feedback from your customers early and often." This is another way of saying that you need to understand your target market and their needs.
Overall, while the book does not explicitly mention the need for an ideal customer profile, it does emphasize the importance of understanding your target market and their needs. This is essentially what an ideal customer profile is.

 

Here are some additional tips for creating an ideal customer profile:
Identify your target market. Who are you trying to sell to? What are their demographics? What are their needs and wants?
Research your target market. What are they reading? What are they talking about online? What are their pain points?
Create a persona. Once you have a good understanding of your target market, create a persona. This is a fictional representation of your ideal customer.

 

Use your ideal customer profile to guide your marketing and sales efforts. Use your persona to create content, develop marketing campaigns, and target your sales efforts.

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Did Open AI Open Pandora's Box?

Pandora opening the box that releases  harm into the world. Image at: https://nypl.getarchive.net/media/pandora-opens-the-box-ca3915

OpenAI not only democratized access to AI but popularized it by inviting people to use it for free. Many of us have opened that box, but some of us have been dismayed at the results that speak as if they are objective truth without any accountability for sources of information or explanation for how ChatGPT arrives at its conclusion.

Relying on AI as an objective source of information ignores the fact that it reflects the bias embedded by its human programmers and can reinforce discriminatory effects. The consequences of that can range from biased beauty standards to reinforcing illegal discriminatory practices.  

Now that it just costs $20 a month or can even be available for free at off-peak times, everyone can -- and many are -- make use of ChatGPT instead of doing research in a variety of sources with documentation that offers at least some level of accountability that is essential for explainable AI. 

Read more here:  https://www.linkedin.com/pulse/did-open-ai-pandoras-box-write-way-pro/?trackingId=E3yor3MrHAi2B2HwIdqlVQ%3D%3D

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http://uncommoncontent.blogspot.com/2021/01/the-original-selection-of-11-ai-quotes.html

 

Coke' Misappropriates Vermeer With AI

A 3D billboard at Guarulhos International Airport in Sao Paulo is showcases  Coca-Cola's "Masterpiece" campaign by animating Vermeer's  "Girl with a Pearl Earring" as a girl whose life purpose it is to put bottles of Coke into a pipe that leads to the vending machine for the soft drink. 

This is not "real magic TM" as the Coke video declares. It is a travesty of art that reduces a masterpiece to a Disney-style short film. 

I can just picture the thought process behind this with a discussion of the creative team that went like this:

Rich: We need something everyone recognizes as a masterpiece!

Josh: But it has to not be under copyright!

Rich: Right! 

Dave: How about Mona Lisa?

Rich Maybe, but can we find something else?

Dave: Vermeer!

Rich: What?

Dave:  ChatGPT says one of his paintings is really famous because there was a movie about it.

Josh: Oh, yeah, "Girl With a Pearl Earring." So long as that's not under copyright, it should be good. 

Rich: Yeah, any woman in a famous piece of art acting as a waitress to get you to buy Coke should work.  

High fives all around.

And so you have it. The enigmatic subject of Vermeer's masterpiece is reduced to Disney-heroine-as-serving girl to allow Coke to appropriate high culture to sell you brown-colored carbonated water filled with ingredients that are detrimental to your health.

I'm fine with a brand promoting itself and with showing off 3D effects and other high tech. But it should have gone the route of creating its own character for this rather than stealing art that is not copyright protected.

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MAJOR MARKETING MISSTEPS FROM ADIDAS, M&M'S AND COKE

How chatbots have evolved

 

The origins of the chatbot

The proliferation of chatbots over the last decade may give the impression that they are only a product of the internet. In truth, though, the roots go all the way back to 1966 when Joseph Weizenbaum a German computer scientist and Professor at Massachusetts Institute of Technology developed a program he called ELIZA.

The all caps make it look like an acronym, but ELIZA doesn’t stand for anything. Instead, as explained in the original Stanford article about it: “Its name was chosen to emphasize that it may be incrementally improved by its users, since its language abilities may be continually improved by a ‘teacher.’”

The reference there was to the character of Eliza in George Bernard Shaw’s Pygmalion (more likely recognized by people today as the character in the musical version My Fair Lady). Eliza was hoping to convince others that she was something she was not -- a well-bred lady. Likewise, the program was designed to come across as a human therapist and convince users “that they were having a conversation with a real human being.”

While ELIZA definitely counts as the first chatterbot, the term was only born decades later. In 1994

Michael Maudlin invented a program he named Julia and called the function of a chattering robot “ChatterBot,” and the term soon got shortened to chatbot. 

Chatbots now
While users enjoyed their conversations with those early chatbots, most of us would not mistake them for actual people. But today’s chatbots are a different story. 

They’re able to carry on much more natural-sounding conversations thanks to the application of machine learning, artificial intelligence , and natural language processing. Adding in ML and AI enables them to learn by identifying data patterns and then to apply their knowledge to answer questions and carry out tasks without any human intervention. 

Their greater functionality translates into far more use by businesses and their customers. Today businesses use bots for a range of communication needs, ranging from customer service to product suggestion, scheduling, and various forms of marketing designed to engage the audience.

But the biggest area of growth for chatbots may be in sales. In Chatbots: Vendor Opportunities & Market Forecasts 2020-2024, Juniper Research anticipates consumer retail spend over chatbots will hit $142 billion by 2024, quite a jump from the $2.8 billion we had in 2019.

Juniper also predicts that by 2024 more than half of retail chatbot interactions will go through automatically and that “80% of global consumer spend over chatbots will be attributable to discrete chatbots” that are used through a mobile app rather than a browser. 

On that basis, the report “urges retailers to implement chatbots as part of a wider omnichannel retail strategy in order to maximise their presence on a number of key retail channels.”

Read more in  Choose Your Chatbot Wisely

Diversity produces better quality for AI

Artificial Intelligence (AI) is no longer just a projection into future uses but a part of business practices. Machine learning (ML) is a tool used by businesses for predictive modeling that is used in an array of industries, from healthcare to finance to security.

The question that businesses have to address is: Are we being careful to not misuse AI by having it reinforce human biases in the training data?

To get insight into the various factors that play into that assurance, Martine Bertrand, Lead AI at Samasource in Montreal shared her thoughts. Bertrand holds a Ph.D. in physics and has applied her scientific rigor to ML and AI.

The Source of Bias

Bertrand concurs with what other experts have pointed out: “The model doesn’t choose to have a bias,” but rather she said it: “learns from the data it is exposed to.” Consequently a data set that is biased toward a certain category, class, gender, or color of skin will likely produce an inaccurate model.

We saw several examples of such biased models in Can AI Have Biases? Bertrand referred to one of the instances, that of Amazon’s Rekognition. It came under fire over a year ago when Joy Buolamnwini focused her research on its effects.

Buolamnwini found that while Rekognition did have 100% accuracy in recognizing light-skinned males and 98.7% accuracy even for darker males, the accuracy dropped to 92.9% for women with light skin and just 68.6% accuracy for darker-skinned women

Despite the demand for its removal from law enforcement agencies, the software remained in use. Bertrand finds that outrageous because of the potential danger inherent in relying on biased outcomes in that context.

Read more in  Why Diversity is Essential for Quality Data to Train AI